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Background: There is a well-established cross-sectional association between income and health, but estimates of the causal effects of income vary substantially. Different definitions of income may lead to substantially different empirical results, yet research is often framed as investigating "the effect of income" as if it were a single, easily definable construct., Methods/results: The aim of this paper is to introduce a taxonomy for definitional and conceptual issues in studying individual- or household-level income for health research. We focus on (1) the definition of the income measure (earned and unearned; net, gross, and disposable; real and nominal; individual and household; relative and absolute income) and (2) the definition of the causal contrast (amount, functional form assumptions/transformations, direction, duration of change, and timing of exposure and follow-up). We illustrate the application of the taxonomy to four examples from the published literature., Conclusions: Quantified estimates of causal effects of income on health and wellbeing have crucial relevance for policymakers to anticipate the consequences of policies targeting the social determinants of health. However, much prior evidence has been limited by lack of clarity in distinguishing between different causal questions. The present framework can help researchers explicitly and precisely articulate income-related exposures and causal questions., (© 2024. The Author(s).)

Background: Population mental health in the United Kingdom (UK) has deteriorated, alongside worsening socioeconomic conditions, over the last decade. Policies such as Universal Basic Income (UBI) have been suggested as an alternative economic approach to improve population mental health and reduce health inequalities. UBI may improve mental health (MH), but to our knowledge, no studies have trialled or modelled UBI in whole populations. We aimed to estimate the short-term effects of introducing UBI on mental health in the UK working-age population., Methods and Findings: Adults aged 25 to 64 years were simulated across a 4-year period from 2022 to 2026 with the SimPaths microsimulation model, which models the effects of UK tax/benefit policies on mental health via income, poverty, and employment transitions. Data from the nationally representative UK Household Longitudinal Study were used to generate the simulated population (n = 25,000) and causal effect estimates. Three counterfactual UBI scenarios were modelled from 2023: "Partial" (value equivalent to existing benefits), "Full" (equivalent to the UK Minimum Income Standard), and "Full+" (retaining means-tested benefits for disability, housing, and childcare). Likely common mental disorder (CMD) was measured using the General Health Questionnaire (GHQ-12, score ≥4). Relative and slope indices of inequality were calculated, and outcomes stratified by gender, age, education, and household structure. Simulations were run 1,000 times to generate 95% uncertainty intervals (UIs). Sensitivity analyses relaxed SimPaths assumptions about reduced employment resulting from Full/Full+ UBI. Partial UBI had little impact on poverty, employment, or mental health. Full UBI scenarios practically eradicated poverty but decreased employment (for Full+ from 78.9% [95% UI 77.9, 79.9] to 74.1% [95% UI 72.6, 75.4]). Full+ UBI increased absolute CMD prevalence by 0.38% (percentage points; 95% UI 0.13, 0.69) in 2023, equivalent to 157,951 additional CMD cases (95% UI 54,036, 286,805); effects were largest for men (0.63% [95% UI 0.31, 1.01]) and those with children (0.64% [95% UI 0.18, 1.14]). In our sensitivity analysis assuming minimal UBI-related employment impacts, CMD prevalence instead fell by 0.27% (95% UI -0.49, -0.05), a reduction of 112,228 cases (95% UI 20,783, 203,673); effects were largest for women (-0.32% [95% UI -0.65, 0.00]), those without children (-0.40% [95% UI -0.68, -0.15]), and those with least education (-0.42% [95% UI -0.97, 0.15]). There was no effect on educational mental health inequalities in any scenario, and effects waned by 2026. The main limitations of our methods are the model's short time horizon and focus on pathways from UBI to mental health solely via income, poverty, and employment, as well as the inability to integrate macroeconomic consequences of UBI; future iterations of the model will address these limitations., Conclusions: UBI has potential to improve short-term population mental health by reducing poverty, particularly for women, but impacts are highly dependent on whether individuals choose to remain in employment following its introduction. Future research modelling additional causal pathways between UBI and mental health would be beneficial., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Thomson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Policy Points Income is thought to impact a broad range of health outcomes. However, whether income inequality (how unequal the distribution of income is in a population) has an additional impact on health is extensively debated. Studies that use multilevel data, which have recently increased in popularity, are necessary to separate the contextual effects of income inequality on health from the effects of individual income on health. Our systematic review found only small associations between income inequality and poor self-rated health and all-cause mortality. The available evidence does not suggest causality, although it remains methodologically flawed and limited, with very few studies using natural experimental approaches or examining income inequality at the national level., Context: Whether income inequality has a direct effect on health or is only associated because of the effect of individual income has long been debated. We aimed to understand the association between income inequality and self-rated health (SRH) and all-cause mortality (mortality) and assess if these relationships are likely to be causal., Methods: We searched Medline, ISI Web of Science, Embase, and EconLit (PROSPERO: CRD42021252791) for studies considering income inequality and SRH or mortality using multilevel data and adjusting for individual-level socioeconomic position. We calculated pooled odds ratios (ORs) for poor SRH and relative risk ratios (RRs) for mortality from random-effects meta-analyses. We critically appraised included studies using the Risk of Bias in Nonrandomized Studies - of Interventions tool. We assessed certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation framework and causality using Bradford Hill (BH) viewpoints., Findings: The primary meta-analyses included 2,916,576 participants in 38 cross-sectional studies assessing SRH and 10,727,470 participants in 14 cohort studies of mortality. Per 0.05-unit increase in the Gini coefficient, a measure of income inequality, the ORs and RRs (95% confidence intervals) for SRH and mortality were 1.06 (1.03-1.08) and 1.02 (1.00-1.04), respectively. A total of 63.2% of SRH and 50.0% of mortality studies were at serious risk of bias (RoB), resulting in very low and low certainty ratings, respectively. For SRH and mortality, we did not identify relevant evidence to assess the specificity or, for SRH only, the experiment BH viewpoints; evidence for strength of association and dose-response gradient was inconclusive because of the high RoB; we found evidence in support of temporality and plausibility., Conclusions: Increased income inequality is only marginally associated with SRH and mortality, but the current evidence base is too methodologically limited to support a causal relationship. To address the gaps we identified, future research should focus on income inequality measured at the national level and addressing confounding with natural experiment approaches., (© 2024 The Authors. The Milbank Quarterly published by Wiley Periodicals LLC on behalf of The Milbank Memorial Fund.)

Background: Employment and income are important determinants of mental health (MH), but the extent that unemployment effects are mediated by reduced income is unclear. We estimated the total effect (TE) of unemployment on MH and the controlled direct effect (CDE) not acting via income., Methods: We included adults 25-64 years from nine waves of the UK Household Longitudinal Study ( n = 45 497/ obs = 202 297). Unemployment was defined as not being in paid employment; common mental disorder (CMD) was defined as General Health Questionnaire-12 score ≥4. We conducted causal mediation analysis using double-robust marginal structural modelling, estimating odds ratios (OR) and absolute differences for effects of unemployment on CMD in the same year, before (TE) and after (CDE) blocking the income pathway. We calculated percentage mediation by income, with bootstrapped standard errors., Results: The TE of unemployment on CMD risk was OR 1.66 (95% CI 1.57-1.76), with 7.09% (6.21-7.97) absolute difference in prevalence; equivalent CDEs were OR 1.55 (1.46-1.66) and 6.08% (5.13-7.03). Income mediated 14.22% (8.04-20.40) of the TE. Percentage mediation was higher for job losses [15.10% (6.81-23.39)] than gains [8.77% (0.36-17.19)]; it was lowest for those 25-40 years [7.99% (-2.57 to 18.51)] and in poverty [2.63% (-2.22 to 7.49)]., Conclusions: A high proportion of the short-term effect of unemployment on MH is not explained by income, particularly for younger people and those in poverty. Population attributable fractions suggested 16.49% of CMD burden was due to unemployment, with 13.90% directly attributable to job loss rather than resultant income changes. Similar analytical approaches could explore how this differs across contexts, by other factors, and consider longer-term effects.

Background: Many complex public health evidence gaps cannot be fully resolved using only conventional public health methods. We aim to familiarise public health researchers with selected systems science methods that may contribute to a better understanding of complex phenomena and lead to more impactful interventions. As a case study, we choose the current cost-of-living crisis, which affects disposable income as a key structural determinant of health., Methods: We first outline the potential role of systems science methods for public health research more generally, then provide an overview of the complexity of the cost-of-living crisis as a specific case study. We propose how four systems science methods (soft systems, microsimulation, agent-based and system dynamics models) could be applied to provide more in-depth understanding. For each method, we illustrate its unique knowledge contributions, and set out one or more options for studies that could help inform policy and practice responses., Results: Due to its fundamental impact on the determinants of health, while limiting resources for population-level interventions, the cost-of-living crisis presents a complex public health challenge. When confronted with complexity, non-linearity, feedback loops and adaptation processes, systems methods allow a deeper understanding and forecasting of the interactions and spill-over effects common with real-world interventions and policies., Conclusions: Systems science methods provide a rich methodological toolbox that complements our traditional public health methods. This toolbox may be particularly useful in early stages of the current cost-of-living crisis: for understanding the situation, developing solutions and sandboxing potential responses to improve population health., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: Home working has increased since the Coronavirus Disease 2019 (COVID-19) pandemic's onset with concerns that it may have adverse health implications. We assessed the association between home working and social and mental wellbeing among the employed population aged 16 to 66 through harmonised analyses of 7 UK longitudinal studies., Methods and Findings: We estimated associations between home working and measures of psychological distress, low life satisfaction, poor self-rated health, low social contact, and loneliness across 3 different stages of the pandemic (T1 = April to June 2020 -first lockdown, T2 = July to October 2020 -eased restrictions, T3 = November 2020 to March 2021 -second lockdown) using modified Poisson regression and meta-analyses to pool results across studies. We successively adjusted the model for sociodemographic characteristics (e.g., age, sex), job characteristics (e.g., sector of activity, pre-pandemic home working propensities), and pre-pandemic health. Among respectively 10,367, 11,585, and 12,179 participants at T1, T2, and T3, we found higher rates of home working at T1 and T3 compared with T2, reflecting lockdown periods. Home working was not associated with psychological distress at T1 (RR = 0.92, 95% CI = 0.79 to 1.08) or T2 (RR = 0.99, 95% CI = 0.88 to 1.11), but a detrimental association was found with psychological distress at T3 (RR = 1.17, 95% CI = 1.05 to 1.30). Study limitations include the fact that pre-pandemic home working propensities were derived from external sources, no information was collected on home working dosage and possible reverse association between change in wellbeing and home working likelihood., Conclusions: No clear evidence of an association between home working and mental wellbeing was found, apart from greater risk of psychological distress during the second lockdown, but differences across subgroups (e.g., by sex or level of education) may exist. Longer term shifts to home working might not have adverse impacts on population wellbeing in the absence of pandemic restrictions but further monitoring of health inequalities is required., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: SVK is a member of the Scientific Advisory Group on Emergencies, the other authors report no competing interests., (Copyright: © 2023 Wels et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Addressing poverty through taxation or welfare policies is likely important for public mental health; however, few studies assess poverty's effects using causal epidemiology. We estimated the effect of poverty on mental health., Methods: We used data on working-age adults (25-64 years) from nine waves of the UK Household Longitudinal Survey (2009-19; n = 45 497/observations = 202 207 following multiple imputation). We defined poverty as a household equivalized income <60% median, and the outcome likely common mental disorder (CMD) as a General Health Questionnaire-12 score ≥4. We used double-robust marginal structural modelling with inverse probability of treatment weights to generate absolute and relative effects. Supplementary analyses separated transitions into/out of poverty, and stratified by gender, education, and age. We quantified potential impact through population attributable fractions (PAFs) with bootstrapped standard errors., Results: Good balance of confounders was achieved between exposure groups, with 45 830 observations (22.65%) reporting poverty. The absolute effect of poverty on CMD prevalence was 2.15% [%-point change; 95% confidence interval (CI) 1.45, 2.84]; prevalence in those unexposed was 20.59% (95% CI 20.29%, 20.88%), and the odds ratio was 1.17 (95% CI 1.12, 1.24). There was a larger absolute effect for transitions into poverty [2.46% (95% CI 1.56, 3.36)] than transitions out of poverty [-1.49% (95% CI -2.46, -0.53)]. Effects were also slightly larger in women than men [2.34% (95% CI 1.41, 3.26) versus 1.73% (95% CI 0.72, 2.74)]. The PAF for moving into poverty was 6.34% (95% CI 4.23, 8.45)., Conclusions: PAFs derived from our causal estimates suggest moves into poverty account for just over 6% of the burden of CMD in the UK working-age population, with larger effects in women., (© The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: On the 1st of May 2018 Scotland became the first country to introduce minimum unit pricing (MUP) for alcohol sales. The objective of this study is to identify the effects of this policy instrument on food purchasing by evaluating a natural experiment., Methods: Longitudinal analysis compares regions with similar characteristics but differing exposure to MUP (Scotland and the north of England). Secondary data from the Kantar Worldpanel on itemised purchases between April 2017 and April 2019 provided a total sample of 8051 households. The outcomes analysed are weekly household expenditure (£s) and purchase volume (grams), both overall and disaggregated to 16 product categories., Results: Following the introduction of MUP, total household food expenditure in Scotland declined by 1.0%, 95%CI [-1.9%, -0.0%], and total food volume declined by 0.8%, 95%CI [-1.7%, 0.2%] compared to the north of England. There is variation in response between product categories, with less spending on fruit and vegetables and increased spending on crisps and snacks., Conclusion: Minimum unit pricing for alcohol has displaced some household food purchasing and the pattern of changes in food categories appears to be less desirable from a healthy diet perspective. However, changes caused by a minimum price at a nominal 50 pence per unit of alcohol are relatively small., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)

Objectives: Taxes and restrictions on promotions have recently been proposed as policy instruments to reduce consumption of unhealthy foods. The objective of this study is to add to the limited evidence on the comparative effectiveness of price changes, price promotions and volume promotions in changing household purchasing of unhealthy foods, using biscuits, crisps and savoury snacks as examples., Design: Longitudinal regression analysis of consumer microdata., Setting: Secondary data on itemised household purchases of biscuits, crisps and savoury snacks from 2006 to 2012., Participants: Sample of 3024 households in Scotland., Main Outcome Measures: Changes in the number of calories (kcal) purchased in the product category by a household caused by changes in the price for the product category, any temporary in-store price promotions and any temporary in-store volume promotions. Changes are measured at the mean, median, 25th percentile and 75th percentile of the household purchasing distribution for the full sample. Subgroup analyses were conducted by household income band and for households with and without children., Results: Between product categories, the scale of purchasing response to incentives varies significantly. Within product categories, the mean calories (kcal) purchased by a household are more responsive to any volume promotion than to price or any price promotion for all product categories. As the volume of items purchased increases, households are less responsive to price, less responsive to any volume promotion and more responsive to any price promotion. Statistically significant differences are observed between household income groups in their response to price and promotion incentives within the biscuits category only. In cases where statistically significant differences are observed, households with children are more responsive to promotion and price incentives than households without children., Conclusions: For all product categories analysed (biscuits, crisps and savoury snacks), household purchasing is most responsive to any volume promotion. Therefore, assuming the response of consumers to incentives remains constant following legislation, the most effective policy instrument to reduce the calorie intake from these products may be a ban on volume promotions., Competing Interests: Competing interests: This work was supported by the Scottish Government Rural and Environment Science and Analytical Services division and the Chief Scientist Office of the Scottish Government Health and Social Care Directorates., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Policymakers are becoming aware that increasing the size of the healthcare workforce is no longer the most viable way to address the increasing demand for healthcare. Consequently, a focus of recent healthcare workforce reform has been extending existing roles and creating new roles for health professionals. However, little is known of the influence on outcomes from this variation in labour inputs within hospital production functions. Using a unique combination of primary and administrative data, this paper provides evidence of associations between the composition of care delivery teams and patient outcomes. The primary data enabled the construction of a task component-based measure of skill mix. This novel measure of skill mix has the advantage of capturing how workforce planning can restructure the relative input of nurses or physicians into task components while keeping the overall level of staff fixed. The analysis focuses on specific care pathways and individual hospitals, thus controlling for an under-investigated source of heterogeneity. Additionally, stratifying by country (England, Scotland, and Norway) enabled analysis of skill mix within different health systems. We provide evidence that variations in labour inputs within the breast cancer and heart disease care pathways are associated with both positive and adverse outcomes. The results illustrate the scope for substitution of task components within care pathways as a potential method of healthcare reform., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Objectives: The usefulness of discrete choice experiments (DCEs) to inform clinical guidelines rests on the assumption that patients facing the same treatment choice at different points in time will express the same preferences. This study provides the first investigation, to our knowledge, to specifically focus on the stability of patients' treatment preferences over the course of a clinical trial., Methods: The same DCE was completed by participants at baseline and final post-treatment assessment in a trial of the efficacy of alternative topical treatments for actinic keratosis as a means for the prevention of skin cancer. The study assesses both the consistency of stated treatment choices and the stability of population-level preference parameter estimates and analyzes how the former is influenced by design aspects of the DCE., Results: No evidence was found of population-level preference parameter instability over the course of the trial despite only a moderate strength of choice consistency. Choice consistency is negatively related to task difficulty with weak evidence of the existence of ordering effects over the sequence of choice tasks., Conclusions: The results provide no evidence that the timing of a DCE within a clinical trial significantly influences population-level treatment preference estimates., (Copyright © 2020 ISPOR–The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. All rights reserved.)

Economic insecurity is an emerging topic that is increasingly relevant to the labour markets of developed economies. This paper uses data from the British Household Panel Survey to assess the causal effect of various aspects of economic insecurity on mental health in the UK. The results support the idea that economic insecurity is an emerging socioeconomic determinant of mental health, although the size of the effect varies across measures of insecurity. In particular, perceived future risks are more damaging to mental health than realised volatility, insecurity is more damaging for men, and the negative effect of insecurity is constant throughout the income distribution. Importantly, these changes in mental health are experienced without future unemployment necessarily occurring.